Search Results - "Nahmias, Mitchell A"

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  1. 1

    Neuromorphic photonic networks using silicon photonic weight banks by Tait, Alexander N., de Lima, Thomas Ferreira, Zhou, Ellen, Wu, Allie X., Nahmias, Mitchell A., Shastri, Bhavin J., Prucnal, Paul R.

    Published in Scientific reports (07-08-2017)
    “…Photonic systems for high-performance information processing have attracted renewed interest. Neuromorphic silicon photonics has the potential to integrate…”
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  2. 2

    Photonic Multiply-Accumulate Operations for Neural Networks by Nahmias, Mitchell A., de Lima, Thomas Ferreira, Tait, Alexander N., Peng, Hsuan-Tung, Shastri, Bhavin J., Prucnal, Paul R.

    “…It has long been known that photonic communication can alleviate the data movement bottlenecks that plague conventional microelectronic processors. More…”
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  3. 3

    Digital Electronics and Analog Photonics for Convolutional Neural Networks (DEAP-CNNs) by Bangari, Viraj, Marquez, Bicky A., Miller, Heidi, Tait, Alexander N., Nahmias, Mitchell A., de Lima, Thomas Ferreira, Peng, Hsuan-Tung, Prucnal, Paul R., Shastri, Bhavin J.

    “…Convolutional Neural Networks (CNNs) are powerful and highly ubiquitous tools for extracting features from large datasets for applications such as computer…”
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    Feedback control for microring weight banks by Tait, Alexander N, Jayatilleka, Hasitha, De Lima, Thomas Ferreira, Ma, Philip Y, Nahmias, Mitchell A, Shastri, Bhavin J, Shekhar, Sudip, Chrostowski, Lukas, Prucnal, Paul R

    Published in Optics express (01-10-2018)
    “…Microring weight banks present novel opportunities for reconfigurable, high-performance analog signal processing in photonics. Controlling microring filter…”
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  5. 5

    A Leaky Integrate-and-Fire Laser Neuron for Ultrafast Cognitive Computing by Nahmias, M. A., Shastri, B. J., Tait, A. N., Prucnal, P. R.

    “…We propose an original design for a neuron-inspired photonic computational primitive for a large-scale, ultrafast cognitive computing platform. The laser…”
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  6. 6

    Progress in neuromorphic photonics by Ferreira de Lima, Thomas, Shastri, Bhavin J., Tait, Alexander N., Nahmias, Mitchell A., Prucnal, Paul R.

    Published in Nanophotonics (Berlin, Germany) (11-03-2017)
    “…As society’s appetite for information continues to grow, so does our need to process this information with increasing speed and versatility. Many believe that…”
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  7. 7

    Primer on silicon neuromorphic photonic processors: architecture and compiler by Ferreira de Lima, Thomas, Tait, Alexander N., Mehrabian, Armin, Nahmias, Mitchell A., Huang, Chaoran, Peng, Hsuan-Tung, Marquez, Bicky A., Miscuglio, Mario, El-Ghazawi, Tarek, Sorger, Volker J., Shastri, Bhavin J., Prucnal, Paul R.

    Published in Nanophotonics (Berlin, Germany) (01-10-2020)
    “…Microelectronic computers have encountered challenges in meeting all of today’s demands for information processing. Meeting these demands will require the…”
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  8. 8

    Broadcast and Weight: An Integrated Network For Scalable Photonic Spike Processing by Tait, Alexander N., Nahmias, Mitchell A., Shastri, Bhavin J., Prucnal, Paul R.

    Published in Journal of lightwave technology (01-11-2014)
    “…We propose an on-chip optical architecture to support massive parallel communication among high-performance spiking laser neurons. Designs for a network…”
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  9. 9

    Scalable Wideband Principal Component Analysis via Microwave Photonics by Ferreira de Lima, Thomas, Tait, Alexander N., Nahmias, Mitchell A., Shastri, Bhavin J., Prucnal, Paul R.

    Published in IEEE photonics journal (01-04-2016)
    “…Microwave photonics (MWP) provides advantages in bandwidth performance and fan-in scalability that are far superior to electronic counterparts. Processing of…”
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  10. 10

    Machine Learning With Neuromorphic Photonics by de Lima, Thomas Ferreira, Peng, Hsuan-Tung, Tait, Alexander N., Nahmias, Mitchell A., Miller, Heidi B., Shastri, Bhavin J., Prucnal, Paul R.

    Published in Journal of lightwave technology (01-03-2019)
    “…Neuromorphic photonics has experienced a recent surge of interest over the last few years, promising orders of magnitude improvements in both speed and energy…”
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    Spike processing with a graphene excitable laser by Shastri, Bhavin J., Nahmias, Mitchell A., Tait, Alexander N., Rodriguez, Alejandro W., Wu, Ben, Prucnal, Paul R.

    Published in Scientific reports (12-01-2016)
    “…Novel materials and devices in photonics have the potential to revolutionize optical information processing, beyond conventional binary-logic approaches. Laser…”
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  12. 12

    Demonstration of WDM weighted addition for principal component analysis by Tait, Alexander N, Chang, John, Shastri, Bhavin J, Nahmias, Mitchell A, Prucnal, Paul R

    Published in Optics express (18-05-2015)
    “…We consider an optical technique for performing tunable weighted addition using wavelength-division multiplexed (WDM) inputs, the enabling function of a…”
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  13. 13

    Multi-channel control for microring weight banks by Tait, Alexander N, de Lima, Thomas Ferreira, Nahmias, Mitchell A, Shastri, Bhavin J, Prucnal, Paul R

    Published in Optics express (18-04-2016)
    “…We demonstrate 4-channel, 2GHz weighted addition in a silicon microring filter bank. Accurate analog weight control becomes more difficult with increasing…”
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  14. 14

    Temporal Information Processing With an Integrated Laser Neuron by Peng, Hsuan-Tung, Angelatos, Gerasimos, de Lima, Thomas Ferreira, Nahmias, Mitchell A., Tait, Alexander N., Abbaslou, Siamak, Shastri, Bhavin J., Prucnal, Paul R.

    “…Spiking neural networks enable efficient information processing in real-time. Excitable lasers can exhibit ultrafast spiking dynamics, and when preceded by a…”
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  15. 15

    Excitable laser processing network node in hybrid silicon: analysis and simulation by Nahmias, Mitchell A, Tait, Alexander N, Shastri, Bhavin J, de Lima, Thomas Ferreira, Prucnal, Paul R

    Published in Optics express (05-10-2015)
    “…The combination of ultrafast laser dynamics and dense on-chip multiwavelength networking could potentially address new domains of real-time signal processing…”
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  16. 16

    Noise Analysis of Photonic Modulator Neurons by de Lima, Thomas Ferreira, Tait, Alexander N., Saeidi, Hooman, Nahmias, Mitchell A., Peng, Hsuan-Tung, Abbaslou, Siamak, Shastri, Bhavin J., Prucnal, Paul R.

    “…Neuromorphic photonics relies on efficiently emulating analog neural networks at high speeds. Prior work showed that transducing signals from the optical to…”
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  17. 17

    Power Transfer Function Tailoring in a Highly Ge-Doped Nonlinear Interferometer-Based All-Optical Thresholder Using Offset-Spectral Filtering by Rafidi, N. S., Kravtsov, K. S., Yue Tian, Fok, M. P., Nahmias, M. A., Tait, A. N., Prucnal, P. R.

    Published in IEEE photonics journal (01-04-2012)
    “…We experimentally investigate and characterize the improvement in thresholding capability of a compact highly Ge-doped nonlinear interferometer-based…”
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    SIMPEL: circuit model for photonic spike processing laser neurons by Shastri, Bhavin J, Nahmias, Mitchell A, Tait, Alexander N, Wu, Ben, Prucnal, Paul R

    Published in Optics express (23-03-2015)
    “…We propose an equivalent circuit model for photonic spike processing laser neurons with an embedded saturable absorber—a simulation model for photonic…”
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    Photonic Implementation of Spike-Timing-Dependent Plasticity and Learning Algorithms of Biological Neural Systems by Toole, Ryan, Tait, Alexander N., Ferreira de Lima, Thomas, Nahmias, Mitchell A., Shastri, Bhavin J., Prucnal, Paul R., Fok, Mable P.

    Published in Journal of lightwave technology (15-01-2016)
    “…The neurobiological learning algorithm, spike-timing-dependent plasticity (STDP), is demonstrated in a simple photonic system using the cooperative nonlinear…”
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